Development of VFM scenarios

The VFM scenarios used in this study were developed using the process proposed by Ogilvy and Schwartz (1998, pp. 57-80). They recommend use of groups to ensure

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inclusion of the widest range of views. For this study, the VFM scenarios were developed using the feedback from the reference group (section 5.2.2) and a review of literature on current and future EV and ICEV technologies.

Objective of the scenario analysis

The objective of the scenario analysis in this study was to explore, in a systematic, plausible, and manageable fashion, those factors that affect the demand for EVs in New Zealand, and the types and amount of fuel consumed by the LPV fleet.

The main elements or key factors

Ogilvy & Schwartz group the key factors in scenario analysis into economic, technological, social, and policy categories. The key factors for this study are summarised in Table 5.16.

Table 5.16: Key factors in the scenario analysis

Factors Description

Economic factors

Fuel costs (Price of petrol diesel and electricity) Price (purchase price, battery replacement price)

Future size of the fleet (vehicle ownership) Vehicle age, vehicles entering and leaving the fleet

Technological factors

Availability of EVs (types of EVs and availability of used imports)

Technical performance (range, speed, battery life, energy efficiency)

Endogenous to the model (car buyer preferences determined by discrete choice model) Policy factors

Price of carbon

Availability of public charging infrastructure Incentives to develop or buy vehicle technology

The certainties and uncertainties

Certainties are those factors that are predetermined and are unlikely to vary significantly across the scenarios. For this study, it was assumed that the following factors would be less likely to change in the future and could be held constant across the scenarios:

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 the relationship between GDP per capita and vehicle ownership per capita

 population growth at 0.8% per year

 household size (persons per household)

 real household income (income relative to GDP)

 car buyers’ purchase preferences (as at 2010).

In addition, a number of simplifying assumptions were made:

 the supply of new EVs would be sufficient to meet global and New Zealand demand from 2012

 the current practice of Japan exporting used vehicles would be extended to EVs

 vehicle occupancy remains at current levels.

The uncertainties modelled in this study comprised the:

 rate of progress in the development of EV battery technology

 rate of decline in EV and battery manufacturing costs and subsequent price reductions

 future rate of increase in the driving range of EVs

 future rate of improvement in the fuel/energy consumption of ICEVs and EVs

 future price of petroleum

 future price of carbon

 extent of public EV charging facilities

 type of vehicle charging behaviour of users of EVs.

For this study, it was assumed that car buyers’ preferences will not change over the modelling period. This assumption was made in recognition that it is not easy to predict changes in cultural norms and personal values. However, for the VFM to remain valid it will be necessary to undertake regular stated choice surveys to take better account of these changing values.

153 The official future

The ‘official future’ is defined as the one that decision makers explicitly or implicitly believe will happen. This future generally assumes that there will be no unexpected changes to the current environment and a continuation of current trends (Ogilvy and Schwartz, 1998). The official future is often known as the reference scenario against which other scenarios are assessed.

In this study, the official future scenario was one where the LPV fleet continued to grow until 2030, but there were no new energy or transport policies introduced beyond those currently in force. In this future, due to increasing exploration costs, petroleum prices continued to increase steadily, but there were no supply

constraints resulting in sudden price shocks and the average energy efficiency of ICEVs entering the LPV fleet did not improve. The price on carbon stayed at a relatively low level of $25 per tonne of CO2. Without policy support, the availability of EVs remained constrained and the market share of EVs did not increase.

The scenario matrix

The scenario matrix defines the two most important critical forces or uncertainties of the issue. For this study, the two key uncertainties identified were: (1) the level of support from governments for EVs and other advanced vehicle technologies; and (2) the rate of success in developing EV technology, specifically those research and development breakthroughs that would improve the performance of EV batteries and reduce EV manufacturing costs.

The two axes in Figure 5.18 represent progress in the development of EV technologies and the degree of support for EV and other advanced vehicle technologies.

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Figure 5.18: Scenario matrix

Overview of the VFM scenarios

The scenarios used in this study were informed by the International Energy

Agency’s (IEA) World Energy Outlook 2010 (International Energy Agency, 2010) and the New Zealand Energy Outlook 2010 (Ministry of Economic Development, 2010b).

The IEA produces the World Energy Outlook annually. In the 2010 edition, the IEA presented three scenarios. The Current Policies Scenario represents a “business as usual” view of the future. This scenario assumes the continuation of existing and currently implemented policies to address energy demand and GHG emissions. The New Policies Scenario reflects a future where new policies are introduced, but these policies are relatively cautious. The 450 Scenario reflects a future where the policies implemented will be sufficient to limit CO2e atmospheric concentrations to 450 ppm. This is the level of CO2e atmospheric concentration that the IEA regards as sufficient to limit average global temperature to about 2^oC (International Energy Agency, 2010, p. 53).

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The VFM scenarios in this study were grouped into three scenario families (A, B, and C) informed by the IEA’s current policies, new policies, and 450 scenarios.

These three different views reflect different levels of policy support towards reducing GHG emissions from the LPV fleet, including the level of support that EVs would receive. In the A family, it was assumed that there was no policy support beyond current levels. In the B family, it was assumed that policy support occurred in response to increasing price of petroleum with the support primarily directed towards improving the fuel efficiency of ICEV based technologies. In the C family, it was assumed that there would be early policy intervention that attempted to reduce GHG emissions from LPVs by promoting the use of EVs and high efficiency ICEVs.

Within each scenario family, the VFM scenarios progress from those that took a relatively conservative view of the rate of improvement of EV technologies to those that envisaged more rapid progress.

In New Zealand, the Ministry of Economic Development (MED) prepared, on a regular basis, an Energy Outlook report. The April 2010 version contained what the MED calls a principal scenario, which has the function of a reference scenario. This scenario was used by the MED to assess the effect of different assumptions of projected growth of GDP, fuel prices, currency exchange rates, and GHG emission prices on the projected demand for energy and GHG emissions. The MED has indicated at that time that further scenarios would be developed to explore the effects of different policy options (Ministry of Economic Development, 2010b).

The MED’s Energy Outlook report provided the default GDP, population, currency exchange rates, and electricity price inputs used in the VFM scenarios.

Table 5.17 outlines the overall scheme of the VFM scenarios used in this study and summarises the key features of each scenario. The table indicates those VFM scenarios used for the sensitivity analyses.

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Table 5.17: Overview of the vehicle fleet model scenarios

No technological progress Technological progress Tech break-through

No electric vehicles

High and rapid growth in price of oil based

Lower growth in price of oil based transport fuels

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